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Senior Director Data Science Jobs in Arizona (NOW HIRING)

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Senior Director Data Science information

What does a senior director of data science do?

A Senior Director of Data Science leads and oversees the data science strategy for an organization, managing teams of data scientists, analysts, and engineers. They are responsible for aligning data initiatives with business goals, guiding advanced analytics projects, and ensuring the effective use of data to drive decision-making. This role often involves collaborating with other executives to develop data-driven solutions, establishing best practices, and setting the vision for how data science supports organizational growth.

How does a senior director of data science typically collaborate with other departments within an organization?

A Senior Director of Data Science frequently partners with leaders from product, engineering, marketing, and business strategy to align data-driven insights with organizational goals. They facilitate cross-functional collaboration by translating complex analytics into actionable business recommendations, ensuring that data science initiatives support top-level priorities. This role often leads a team of data scientists while serving as a bridge between technical teams and non-technical stakeholders, fostering a culture of data-informed decision-making throughout the company.

What are the key skills and qualifications needed to thrive as a senior director data science, and why are they important?

To thrive as a Senior Director Data Science, you need deep expertise in advanced analytics, machine learning, statistical modeling, and a strong educational background in a quantitative field, often with a master's or PhD. Familiarity with data platforms (like AWS, Azure), programming languages (such as Python, R), and leadership in deploying enterprise-level data solutions is vital, along with experience managing large teams. Exceptional strategic thinking, communication, and stakeholder management skills set top candidates apart in this role. These abilities are crucial for driving data-driven business strategies, leading high-performing teams, and ensuring impactful outcomes at the organizational level.

What is the difference between Senior Director Data Science vs Data Science Manager?

AspectSenior Director Data ScienceData Science Manager
ResponsibilitiesOversees multiple teams, sets strategic vision, aligns data science initiatives with business goalsManages day-to-day operations of data science teams, executes projects, and ensures deliverables
Required CredentialsAdvanced degree (Master's/PhD), extensive experience, leadership skillsRelevant degree, experience in managing data projects, technical expertise
Work EnvironmentStrategic, cross-departmental, executive collaborationOperational, team-focused, project management

The Senior Director Data Science typically holds a higher strategic leadership role, overseeing multiple teams and aligning data initiatives with company goals. In contrast, a Data Science Manager focuses on managing teams and executing projects. Both roles require strong technical backgrounds, but the Senior Director emphasizes strategic vision and leadership across departments.

What are popular job titles related to Senior Director Data Science jobs in Arizona?

For Senior Director Data Science jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Senior Director Data Science jobs in Arizona look for?

The top searched job categories for Senior Director Data Science jobs in Arizona are:

What cities in Arizona are hiring for Senior Director Data Science jobs?

Cities in Arizona with the most Senior Director Data Science job openings:

Senior Director Data Science jobs near you
Infographic showing various Senior Director Data Science job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, 2% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior AI Engineer / Data Scientist

Koantek

Chandler, AZ • On-site

Contractor

Re-posted 11 days ago

Job description


Senior AI Engineer / Data Scientist (Consulting)
Location: United States (Remote)
Employment Type: Full-Time / Contract
Experience Level: Senior
About the Role:
We are seeking an experienced, highly technical Senior AI Engineer / Data Scientist to join our customer-facing consulting team. This remote role requires a unique blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation.
You will design, deploy, and maintain production-grade ML solutions, including advanced Generative AI and NLP models, for our diverse client base.
Key Responsibilities:
* Technical Consulting: Lead end-to-end ML implementations directly with clients, translating business problems into robust technical solutions.
* MLOps and Pipelines: Design, build, and maintain production-grade ML pipelines with a strong focus on CI/CD, automation, and scalability.
* GenAI and NLP Deployment: Implement and optimize cutting-edge Generative AI applications (such as LLMs and RAG) in live production settings.
* Infrastructure and Data Scale: Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark.
* Stakeholder Management: Clearly communicate technical findings, proposals, and project status to both technical and non-technical audiences.
Required Qualifications:
* 4+ years of professional experience developing, deploying, and maintaining ML models in a live production environment (Mandatory).
* 3+ years of experience in a customer-facing consulting or Solutions Architect role.
* Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, and automated deployment).
* Solid hands-on experience with containerization (Docker) and data pipeline orchestration.
* Proven track record of deploying Generative AI and NLP solutions for client applications.
* Excellent verbal and written communication skills.
Preferred Qualifications:
* Hands-on experience with modern ML platform stacks, specifically Databricks MLOps Stacks.
* Deep knowledge of large-scale data processing and distributed machine learning techniques.
* A strong commitment to continuous learning in emerging ML fields and GenAI application architectures.

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